Abstract
This paper combines the image adaptive threshold denoising algorithm and performs double threshold mapping processing to the infrared image, which effectively reduces the influence of these phenomena to the infrared image and improves the quality of the image. In this paper, the infrared image denoising technology is studied, and an infrared image denoising method based on the wavelet coefficient threshold processing is proposed. This method is based on the noise distribution characteristics of infrared images, the multiplicative noise in the infrared image is transformed into an additive noise, and the wavelet transform coefficient of the transformed infrared image is processed to denoise the image. On this basis, the advantages and disadvantages of the soft and hard threshold functions are deeply analyzed, and an adaptive threshold function with adjustable parameter is constructed. At the same time, in order to suppress the Gibbs visual distortion caused by the absence of translation invariance of the orthogonal wavelet transform, the two-input wavelet transform with translation invariance is introduced, and a double threshold mapping infrared image processing method based on the adaptive threshold denoising algorithm based on the two-input wavelet transform is formed. Simulation results show that the method proposed in this paper has a better suppression of noise, maintains the integrity of image details, and improves the image quality to a certain extent.
Highlights
The infrared image characterizes the thermal properties of the point in the scene with the brightness of each pixel
On the basis of infrared image denoising method based on wavelet coefficient threshold processing, the advantages and disadvantages of soft and hard threshold functions are deeply analyzed, and an adaptive threshold function with adjustable parameters is constructed
5 Conclusions With the implementation of the Digital Earth Project and the development of infrared technology, infrared image processing has become the main factor restricting the development of infrared technology
Summary
Their surface temperature or radiation flux will be inhomogeneous because of their strange shape and structure and many dispersed heat sources. 2. On the basis of infrared image denoising method based on wavelet coefficient threshold processing, the advantages and disadvantages of soft and hard threshold functions are deeply analyzed, and an adaptive threshold function with adjustable parameters is constructed. The experimental results show that the denoised image is better than the traditional soft and hard thresholding and the existing thresholding in terms of visual effect, mean square deviation, and peak signal-to-noise ratio These methods open up a broad prospect for the full advantage of the wavelet threshold denoising method and provide a basis for further exploration of adaptive denoising methods. The results show that translation invariance is an important property of effectively suppressing Gibbs phenomenon and improving denoising effect These conclusions provide a basis for the research of adaptive threshold image denoising based on binary wavelet transform
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